In the industrial fields, the process capability index has been using to evaluate the variation of quality in the process. The traditional process capability indices such as Cp, Cpk, Cpm, and C┼pm have been applied in the industrial fields. These traditional process capability indices are mainly applied in the univariate analysis. However, the main streams in the recent industry are the multivariate manufacturing process and the multiple quality characteristics are corrected each other. Therefore, the multivariate statistical method should be used in the process capability analysis. The multivariate process indices need to be enhanced with more useful information and extensive application in the recent industrial fields. Hence, the purpose of the study is to develop a more effective multivariate process index (MCpI ) using the multivariate inverted normal loss function. The multivariate inverted normal loss function has the flexibility for the any type of the symmetrical and asymmetrical loss functions as well as the economic information. Especially, the proposed modeling method for the multivariate inverted normal loss function (MINLF) and the expected loss from MINLF in this paper can be applied to the any type of the symmetrical and asymmetrical loss functions. And this modeling method can be easily expanded from a bivariate case to a multivariate case.

1. 서 론
 2. 이론적 배경
  2.1 다변량 공정능력지수 MCpm
  2.2 다변량 역정규 손실함수(MINLF)
 3. 연구모형
  3.1 기호
  3.2 다변량 공정능력 지수 MCpI 모형
 4. 수치 예
  4.1 2변량(Bivariate)
  4.2 3변량(Three-Variate)
 5. 결 론
 References

• 문혜진(Department of Industrial and Management Engineering, Incheon National University) | Hye-Jin Moon
• 정영배(Department of Industrial and Management Engineering, Incheon National University) | Young-Bae Chung Corresponding Author